Fig. 3

Each cell presents the cluster centroid separation Δ (brighter colours indicate stronger separation) after multi-dimensional scaling (MDS) was applied to simulated data of 1000 observations and 15 features. Separation is shown as a function of within-feature effect size (Cohen’s d, x-axis), and the proportion of features that were different between clusters. Each row shows a different covariance structure: “mixed” indicates subgroups with different covariance structures, “random” with the same random covariance structure between all groups, and “no” for no correlation between any of the features). Each column shows a different type of population: with unequal (10 and 90%) subgroups, with two equally sized subgroups, and with three equally sized subgroups